A comparative analysis of speech signal processing algorithms for Parkinson's disease classification and the use of the tunable Q-factor wavelet transform.
Cemal Okan SakarGorkem SerbesAysegul GunduzHunkar C. TuncHatice NizamBetul Erdogdu SakarMelih TutuncuTarkan AydinM. Erdem IsenkulHulya ApaydinPublished in: Appl. Soft Comput. (2019)
Keyphrases
- wavelet transform
- classification accuracy
- decision trees
- automatic classification
- pattern recognition
- feature extraction
- classification models
- classification method
- multiresolution
- high frequency
- support vector machine svm
- training samples
- acoustic signals
- speech signal
- classification scheme
- class labels
- machine learning
- image classification
- support vector machine
- support vector
- benchmark datasets
- text classification
- audio visual
- feature space
- factor analysis
- multiscale
- lifting scheme
- image processing